Comprehensions & generators
List/dict/set comprehensions, generator expressions, and lazy iteration.
How to Generate Combinations with Replacement in Python
Generate all r-length combinations with repetition from a list using the standard library itertools.combinations_with_replacement function.
from itertools import combinations_with_replacement
items = ['A', 'B', 'C']
r = 2
combos = list(combinations_with_replacement(items, r))
for combo in combos:
print(combo)
if __name__ == "__main__":
print(f"Total combinations with replacement: {len(combos)}")How to Generate Fibonacci Numbers in Python Without Recursion
Build an efficient infinite Fibonacci sequence using a generator function with O(1) memory and no recursion overhead.
def fib(n):
a, b = 0, 1
for _ in range(n):
yield a
a, b = b, a + b
if __name__ == "__main__":
count = 10
result = list(fib(count))
print(result)How to Generate Permutations of Length r in Python
Generate all ordered arrangements of length r from a given list of elements using itertools.permutations.
from itertools import permutations
def generate_permutations(elements, r):
"""Generate all r-length permutations of the given elements."""
return list(permutations(elements, r))
if __name__ == "__main__":
elements = ['A', 'B', 'C']
r = 2
result = generate_permutations(elements, r)
print(f"Ele…How to Generate Primes with a Generator in Python
Generate prime numbers up to a limit using the Sieve of Eratosthenes wrapped in a generator expression for lazy evaluation.
def prime_generator(limit):
sieve = [True] * (limit + 1)
sieve[0] = sieve[1] = False
for i in range(2, int(limit ** 0.5) + 1):
if sieve[i]:
for j in range(i * i, limit + 1, i):
sieve[j] = False
return (num for num, is_prime in enumerate(sieve) if is_prime)
if __n…How to Group Data in Python with defaultdict and Comprehensions
Group a list of items by a computed key using a defaultdict-based generator helper and an alternative dictionary comprehension approach.
from collections import defaultdict
def group_by(data, key_func):
"""Group items in data by the value returned by key_func."""
result = defaultdict(list)
for item in data:
result[key_func(item)].append(item)
return dict(result)
def group_by_comprehension(data, key_func):
"""Same grouping …How to Implement takewhile Generator in Python
A generator that yields items from an iterable until a condition fails, like itertools.takewhile.
def takewhile(predicate, iterable):
for item in iterable:
if not predicate(item):
break
yield item
if __name__ == "__main__":
numbers = [1, 2, 3, 4, 5, 1, 2, 3]
result = list(takewhile(lambda x: x < 4, numbers))
print(result)How to Lazily Transform Items in Python with a Generator
Map a transform function over an iterable lazily with a generator so items are processed on demand, not up front.
def lazy_map(items, transform):
for item in items:
yield transform(item)
def double(x):
return x * 2
def upper(s):
return s.upper()
if __name__ == "__main__":
numbers = [1, 2, 3, 4, 5]
doubled = lazy_map(numbers, double)
print("Doubled numbers:", end=" ")
for value in doubled:
…How to Merge Multiple Iterables with a Generator in Python
This code defines a generator function that 'chains' or merges multiple iterables into a single iterator, which is then converted to a list.
def chain(*iterables):
for iterable in iterables:
yield from iterable
def main():
list1 = [1, 2, 3]
tuple1 = (4, 5)
set1 = {6, 7}
string1 = "89"
result = list(chain(list1, tuple1, set1, string1))
print(result)
if __name__ == "__main__":
main()How to Parse CSV Rows as Generator Dicts in Python
Reads a CSV file and yields each row as a dictionary one at a time using a generator, so the file is processed lazily.
import csv
from pathlib import Path
def csv_to_dicts(filepath):
with open(filepath, mode="r", newline="", encoding="utf-8") as file:
reader = csv.DictReader(file)
for row in reader:
yield row
if __name__ == "__main__":
sample_csv = Path("sample_data.csv")
sample_csv.write_text…How to Parse Data with Generators and Comprehensions in Python
This code demonstrates using a generator expression to filter active users and a dictionary comprehension to aggregate scores by name.
def parse_data_helper(raw_records):
"""Extract active users' names and scores from raw records."""
parsed = (
(record["name"], record["score"])
for record in raw_records
if record["active"] and record["score"] >= 0
)
return list(parsed)
def aggregate_scores(parsed_data):
"…How to Repeat a Generator Cycle Single Value in Python
Build a generator that repeats a single value across multiple cycles, each cycle adding an extra repetition to mark its completion.
def repeat_with_cycle(value, cycle_limit, repetitions):
"""
Repeats a single value until reaching a cycle limit,
then yields the value one more time to demonstrate a full cycle.
Args:
value: The single value to repeat.
cycle_limit: Number of repetitions per cycle.
repetitio…How to Sort Data with Comprehensions and Generators in Python
Sort a list of tuples by a key, then use a list comprehension to extract names and a generator to square high ranks.
data = [("Anna", 3), ("Ben", 1), ("Clara", 2), ("Dan", 5), ("Eve", 4)]
# Comprehension: list of tuples (name, rank) sorted ascending by rank
sorted_by_rank = sorted(data, key=lambda x: x[1])
# Comprehension: extract just the names in rank order
names_in_rank_order = [name for name, rank in sorted_by_rank]
# Generat…How to Split Data into Chunks and Use Generators in Python
Split a list into fixed-size chunks with a list comprehension and square even numbers lazily with a generator expression.
def split_numbers(data, chunk_size):
return [data[i:i + chunk_size] for i in range(0, len(data), chunk_size)]
def square_even_numbers(numbers):
return (n ** 2 for n in numbers if n % 2 == 0)
if __name__ == "__main__":
sample_data = list(range(1, 21))
chunks = split_numbers(sample_data, 5)
print…How to Throw an Exception into a Python Generator
This code demonstrates how to use the .throw() method on a generator to inject an exception at its current yield point and let it recover gracefully.
def demo_throw_into_generator():
"""Demonstrate throwing an exception into a running generator."""
def counter():
"""Generator that counts until interrupted."""
try:
i = 0
while True:
yield i
i += 1
except ValueError as e:
…How to Use Comprehensions and Generators in Python
Demonstrate list, set, and dictionary comprehensions plus generator expressions and generator functions in one beginner-friendly script.
def demonstrate_comprehensions_generators():
# List comprehension: transform and filter in one line
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
squares = [num ** 2 for num in numbers if num % 2 == 0]
print(f"Square of even numbers (list comprehension): {squares}")
# Set comprehension: unique values
…How to Use Comprehensions and Generators to Check Data in Python
A beginner-friendly helper that filters numeric values, computes squares and cubes with comprehensions and a generator, and returns a summary dictionary.
def check_data(iterable):
"""Return a summary of numeric data using comprehensions and a generator."""
values = [item for item in iterable if isinstance(item, (int, float))]
squares = [x ** 2 for x in values if x > 0]
cubes = (x ** 3 for x in values if x > 0)
cube_list = list(cubes)
return {
…How to Use List Comprehensions and Generators in Python
Analyze a list of numbers using a list comprehension to square evens, a generator for sum, and a generator expression for the maximum squared value.
def analyze_numbers(numbers):
squared = [n ** 2 for n in numbers if n % 2 == 0]
total = sum(n for n in numbers)
max_squared = max((n ** 2 for n in numbers), default=0)
return squared, total, max_squared
if __name__ == "__main__":
data = [1, 2, 3, 4, 5, 6]
evens_squared, total_sum, max_sq = an…How to Use List Comprehensions and Generators to Format Data in Python
A beginner-friendly helper that formats dictionaries into strings using a list comprehension and generates squared numbers lazily with a generator.
def format_data(items):
"""Format a list of dictionaries into readable strings."""
formatted = [
f"{item.get('name', 'Unknown')}: {item.get('value', 0)} units"
for item in items
if item.get('value', 0) > 0
]
return formatted if formatted else ["No positive values found"]
def g…How to Use List Comprehensions and Generators to Transform Data in Python
Transform a list of integers by squaring even numbers with a list comprehension and cubing odd numbers with a generator.
def transform_data(data):
"""
Transform a list of integers:
- squares of even numbers using a list comprehension
- cubes of odd numbers using a generator
"""
squares = [num ** 2 for num in data if num % 2 == 0]
cubes = (num ** 3 for num in data if num % 2 != 0)
return squares, cubes
i…How to Use starmap() to Unpack Tuple Arguments in Python
Use itertools.starmap to apply a function to each tuple in an iterable, unpacking tuple elements as separate arguments and returning an iterator of results.
from itertools import starmap
def multiply(a, b):
return a * b
if __name__ == "__main__":
pairs = [(2, 3), (4, 5), (6, 7), (8, 9)]
results = list(starmap(multiply, pairs))
print(results)How to Validate Data with Python Comprehensions and Generators
Use list, generator, and dictionary comprehensions to filter and transform data for quick validation in Python.
def validate_integer(data):
return [item for item in data if isinstance(item, int)]
def validate_positive(numbers):
return (num for num in numbers if num > 0)
def validate_string_lengths(data, min_length=3):
return {item: len(item) for item in data if isinstance(item, str) and len(item) >= min_length}
i…How to filter a generator with a predicate function in Python
This code defines a generator function that yields only items from an iterable that satisfy a given predicate, then tests it with even and positive number filters.
def filter_gen(predicate, iterable):
for item in iterable:
if predicate(item):
yield item
def is_even(num):
return num % 2 == 0
def is_positive(num):
return num > 0
if __name__ == "__main__":
numbers = range(-5, 10)
even_numbers = list(filter_gen(is_even, numbers))
p…How to filter even numbers with a Python list comprehension
Build a new list of only the even numbers from 1 to 20 using a single list comprehension with a filter condition.
even_numbers = [num for num in range(1, 21) if num % 2 == 0]
print(even_numbers)How to generate combinations in Python with itertools
Generate all unique combinations of r items from a given list using itertools.combinations.
import itertools
def combinations_generator(items, r):
return list(itertools.combinations(items, r))
if __name__ == "__main__":
items = ['A', 'B', 'C', 'D']
r = 2
result = combinations_generator(items, r)
for combo in result:
print(combo)
print(f"Total: {len(result)} combinations of {…Browse by section
Each section groups closely related Python snippets.
Comprehensions & generators — Python code examples
What you will find here
This page collects comprehensions & generators snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.